Volume 88, Issue 1

Today technical electrodes in batteries and fuel cells rely on complex multiphase microstructures that facilitate electronic, ionic and, in case of fuel cells, diffusive gas transport to the active reaction sites distributed in the electrode volume. The impedance of such electrodes can be described by the well-established transmission line model (TLM) approach. In a TLM, transport, charge transfer phenomena and capacitive effects are coupled considering microstructural features of the electrode. Its application for impedance data analysis of technical cells is challenging as the TLM impedance extends over a wide frequency range and quite often a strong overlapping with other contributions takes place. In this paper the application of the distribution of relaxation times (DRT) to the analysis of technical electrodes in batteries and fuel cells is elucidated. Different examples how to apply the DRT to analyze impedance spectra of solid oxide-, polymer electrolyte- and lithium ion-cells will be discussed. It will be shown that the TLM is usually represented by multiple peaks in the DRT, which might be strongly affected if contributions of different electrode layers overlap in the spectra. Related error sources and countermeasures are illustrated. Approaches how the DRT can be applied for the analysis of measured spectra and how it is able to support CNLS-fitting are presented.

Magnetic resonance’s potential is already proven in the clinical sector and for non-destructive testing also in the laboratory environment. With recent developments in technology today’s small and midsized often portable MR systems are also able to work in an industrial setup and in the field. Therefore, the number of MR applications is rapidly increasing as is the acceptance of MR as technique for non-destructive testing. Selected examples for magnetic resonance in polymers, in porous media and in food samples are shown here.

Zusammenfassung In der elektrischen Kapazitätstomografie (ECT) verbessert sich die Auflösung der rekonstruierten Permittivitätsverteilung mit der Elektrodenanzahl, wohingegen die Anzahl der Kapazitätsmessungen und die Messzeit steigt und das Signal-Rausch-Verhältnis sinkt. Um einen Kompromiss zwischen Elektrodenanzahl und Auflösung zu finden, haben wir ein phantomabhängiges Adaptionsverfahren untersucht, in dem grobe Messungen mit verbundenen Einzelelektroden, die quasi synthetische größere Elektroden darstellen, durchgeführt werden. Das Verfahren wurde anhand eines Kunststoffzylinders im Erfassungsbereich im Inneren eines Rohres getestet. Wir vergleichen die rekonstruierten Ergebnisse basierend auf den Kapazitäten zwischen sechs synthetischen Elektroden und zwölf elementaren Elektroden sowie mit dem Adaptionsverfahren, das sowohl die Kapazitäten zwischen den sechs synthetischen Elektroden als auch zwischen einigen der elementaren Kapazitäten auswertet. Die Permittivitätsverteilung wird mit dem projizierten Landweber-Algorithmus einerseits aus berechneten Kapazitäten (Simulation mit der Finite-Elemente-Methode, FEM) und andererseits aus gemessenen Kapazitäten rekonstruiert. Die Kapazitäten werden dabei für jeweils zwei Fälle bestimmt. Im ersten Fall werden die Elektroden, die gerade nicht Teil der betrachteten Kapazität sind, geerdet, im zweiten Fall sind sie potentialfrei. Die Ergebnisse zeigen, dass im Erdungsfall die Rekonstruktionsergebnisse der gemessenen Kapazitäten mit dem Adaptionsverfahren sogar verbessert werden können. Im potentialfreien Fall und bei den Simulationen konnte das Phantom nur mit einer Verschlechterung der Auflösung dargestellt werden.

This paper describes the merging of spectra measured by two different spectrometers. Different concepts for merging data from different instruments are presented. All existing approaches violate the conservation law of energy when comparing measurements from two different instruments. The fundamental cause behind violation of the energy conservation law lies in the properties of the measurement device itself. Data can only be merged successfully if the distortion caused by both instruments is small. Typical real-life examples for spectral measurements are shown and the applicability of merging of the data is evaluated for these cases.

Broken rotor bar (BRB) is one of the most common fault types of induction motors. One of the common methods to detect the broken rotor bars is the observation of the characteristic sideband frequencies in the stator current. If the motor is lightly loaded, the sideband harmonics are attached to the fundamental frequency of the main supply and the amplitudes of these harmonics are quite low. Therefore, it is difficult to detect the broken rotor bars under light loading conditions by using conventional motor current signature analysis (MCSA) methods. Moreover, in some cases, the sideband harmonics of fundamental frequency may exist although there is no rotor fault in induction motors due to load oscillations. Therefore, there is a risk for false broken rotor bars alarm with the existence of lower amplitude of harmonics. This paper provides an alternative approach for the detection of broken rotor bars by applying Hilbert envelope analysis along with Shannon entropy to stator current signals. The proposed method includes two-stage evaluation system to eliminate false BRB alarms such as detecting sidebands from envelope spectrum and calculating entropy rates from envelope signals. The results are verified experimentally under 25 %, 50 %, 75 % and 100 % loading conditions.